Some Informations about the projekt here would be really nice.
Short description of the task at hand.
| Group | Duplication_Rate | Loss_Rate | HGT_Rate | Slope | Intercept | Spearman_Corr |
|---|---|---|---|---|---|---|
| P0 | 0.25 | 0.25 | 0.25 | 0.0014 | 0.23 | 0.21 |
| P1 | 0.50 | 0.50 | 0.50 | -0.0009 | 0.39 | 0.05 |
| P2 | 0.50 | 0.50 | 1.00 | -0.0012 | 0.48 | -0.02 |
| P3 | 0.50 | 0.50 | 1.50 | -0.0021 | 0.58 | -0.16 |
| P4 | 1.00 | 1.00 | 0.50 | -0.0011 | 0.40 | 0.04 |
| P5 | 1.00 | 1.00 | 1.00 | -0.0016 | 0.53 | -0.14 |
| P6 | 1.50 | 1.50 | 1.50 | -0.0016 | 0.57 | -0.24 |
In the following section seven plots are shown which represent the dependency of the Fraction of Xenologs from the Number of Genes. For each group (see Tab. 1) a seperate plot and a linear model was calculated to extract the slope and intercept.
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Genes including a lineare model (red line) with the confidence intervall (grey).
In figure 1 the fraction of xenologs of group \(P0\) is plotted against the number of genes. The linear model shows a positive relationship between those parameters. The slope and intercept are \(0.0014\) and repsectively \(0.23\) with a spearman correlation coefficient of \(0.21\). Figure 2 and 3 show a negative relationship regarding the fraction of xenelogs in dependence of the number of genes. Figure 4 shows the highest negative intercept for all groups (\(-0.0021\)) with a spearman correlation of \(-0.16\). Figures 5 to 7 showing as well a negative relationship between the two parameters, whereas group \(P6\) has the best spearman correlation with \(-0.24\).
CONCLUSION????
Each plot needs a short discription. This can be done here. Maybe it is better not to iterate over the groups. Maybe we should split the following code into \(7\) seperate sektions, so we can write a custom text for each.
| Group | Duplication_Rate | Loss_Rate | HGT_Rate | Slope | Intercept | Spearman_Corr |
|---|---|---|---|---|---|---|
| P0 | 0.25 | 0.25 | 0.25 | 0.0015 | 0.23 | 0.09 |
| P1 | 0.50 | 0.50 | 0.50 | 0.0004 | 0.34 | 0.04 |
| P2 | 0.50 | 0.50 | 1.00 | 0.0004 | 0.42 | 0.02 |
| P3 | 0.50 | 0.50 | 1.50 | -0.0022 | 0.55 | -0.09 |
| P4 | 1.00 | 1.00 | 0.50 | 0.0002 | 0.34 | 0.02 |
| P5 | 1.00 | 1.00 | 1.00 | -0.0016 | 0.49 | -0.04 |
| P6 | 1.50 | 1.50 | 1.50 | 0.0001 | 0.46 | 0.00 |
During the simulation, each tree was given a random number of maximum species ranging from \(10\) to \(50\). In the following section seven plots are shown which represent the dependency of the Fraction of Xenologs from the Number of Species. For each group (see Tab. 2) a seperate plot and a linear model was calculated to calculate the slope and intercept of the dependency.
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
Scatterplot of the Fraction of Xenologs plotted against the Number of Species including a lineare model (red line) with the confidence intervall (grey).
All groups, except \(P3\) and \(P5\), showing a positive correlation regarding the Fraction of Xenologs in dependence o the Number of Species. The result for each group is visualized in Tab. 2. The spearman correlation coefficients range from \(-0.9\) to \(0.09\).
CONCLUSION:
As shown in Tab. 1 and Tab. 2 the duplication and loss rate is increasing in the same rate for each simulation group. Therefore we combine the duplication and loss rate into one factor.
Short introduction- Loss and Duplikation are alwayss the same. Hence just one Figure
Fig. 15: Boxplot of the Fraction of Xenologs plotted against the duplication rate with a fixed horizontal gene transfer (HGT) rate. The different colors marking the groups with the same HGT rate.
In XX we see examples of plotting in R. Explanation of the graph
How does the fraction depend on the horizontal transfer rate on the the rate of duplications and losses?
How does the fraction depend on the horizontal transfer rate with a fixed duplication and loss rate? --> fixed Question??
Boxplot of the Fraction of Xenologs plotted against the HGT rate with a fixed duplikation and loss rate. The different colors marking the groups with the same duplikation or loss rate.
How does the fraction depend on the frequency of multifurctions.
AUCH HIER GEFÄLLT MIR DER PLOTT ÜBERHAUPT NICHT. BOXPLOT ÜBER ALLE GRUPPEN? ODER 6 EINZELNE PLOTS FÜR JEDE GRUPPE MIT LINEAREM ODER x^2 MODEL? ODER WIR BILDEN "BUCKETS" MIT x=NON_BINARY_PROB VS y=FRACTION_OF_XENOLOGS. und wir bilden buckets mit 1 = [0-0.1], 2 = [0.1-0.2], 3 = [0.2-0.3] usw..
caption = "Wasn hier zu sehen??"
plot(x = treeDataDf$non_binary_prob,
y = treeDataDf$Fraction_of_Xenologs)
Wasn hier zu sehen??
Second we consider the dependencies for the edges in Fitch graphs computed from an LDT graph. Here the following variants should be considered:
AsymmeTree).@@Paul, hast du hier nicht schonmal was angefangen?
In meinem Script finde ich dazu nichts.
Die können hier eingefügt werden
The triple set \(T (G)\) is related to the gene tree, while the triple set \(S(G, σ)\) is related to the species tree. It is therefore of interest to compare to what extent \(T (G)\) and \(S(G, σ)\) overlap the triple sets of true gene tree and the triple set of the true species tree, respectively. How can this be quantified in a meaningful way? Again we are interested in the dependence of the simulation parameters.
| Group | recall_cd_mean_100 | recall_cd_mean_80 | recall_cd_mean_60 | recall_cd_mean_40 | recall_cd_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.67 | 0.66 | 0.65 | 0.61 | 0.50 |
| P1 | 0.67 | 0.66 | 0.64 | 0.59 | 0.51 |
| P2 | 0.67 | 0.66 | 0.66 | 0.63 | 0.56 |
| P3 | 0.70 | 0.70 | 0.68 | 0.65 | 0.58 |
| P4 | 0.64 | 0.63 | 0.63 | 0.58 | 0.49 |
| P5 | 0.69 | 0.69 | 0.68 | 0.65 | 0.56 |
| P6 | 0.69 | 0.68 | 0.67 | 0.64 | 0.61 |
| Group | precision_cd_mean_100 | precision_cd_mean_80 | precision_cd_mean_60 | precision_cd_mean_40 | precision_cd_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.85 | 0.86 | 0.89 | 0.88 | 0.87 |
| P1 | 0.88 | 0.88 | 0.91 | 0.91 | 0.90 |
| P2 | 0.91 | 0.92 | 0.93 | 0.93 | 0.94 |
| P3 | 0.94 | 0.95 | 0.95 | 0.96 | 0.96 |
| P4 | 0.86 | 0.87 | 0.88 | 0.88 | 0.89 |
| P5 | 0.93 | 0.93 | 0.94 | 0.94 | 0.93 |
| P6 | 0.95 | 0.95 | 0.95 | 0.95 | 0.97 |
| Group | accuracy_cd_mean_100 | accuracy_cd_mean_80 | accuracy_cd_mean_60 | accuracy_cd_mean_40 | accuracy_cd_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.97 | 0.98 | 0.98 | 0.99 | 1.00 |
| P1 | 0.95 | 0.96 | 0.98 | 0.99 | 1.00 |
| P2 | 0.93 | 0.95 | 0.97 | 0.98 | 1.00 |
| P3 | 0.92 | 0.94 | 0.96 | 0.98 | 0.99 |
| P4 | 0.94 | 0.96 | 0.97 | 0.99 | 1.00 |
| P5 | 0.93 | 0.95 | 0.97 | 0.98 | 1.00 |
| P6 | 0.92 | 0.94 | 0.96 | 0.98 | 0.99 |
| Group | recall_rs_mean_100 | recall_rs_mean_80 | recall_rs_mean_60 | recall_rs_mean_40 | recall_rs_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.70 | 0.67 | 0.65 | 0.62 | 0.51 |
| P1 | 0.71 | 0.69 | 0.65 | 0.59 | 0.53 |
| P2 | 0.73 | 0.70 | 0.69 | 0.66 | 0.58 |
| P3 | 0.75 | 0.74 | 0.72 | 0.67 | 0.60 |
| P4 | 0.70 | 0.66 | 0.66 | 0.60 | 0.52 |
| P5 | 0.74 | 0.73 | 0.71 | 0.67 | 0.58 |
| P6 | 0.75 | 0.74 | 0.72 | 0.68 | 0.64 |
| Group | precision_rs_mean_100 | precision_rs_mean_80 | precision_rs_mean_60 | precision_rs_mean_40 | precision_rs_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.83 | 0.83 | 0.84 | 0.86 | 0.85 |
| P1 | 0.85 | 0.85 | 0.86 | 0.88 | 0.89 |
| P2 | 0.91 | 0.89 | 0.91 | 0.91 | 0.93 |
| P3 | 0.92 | 0.93 | 0.93 | 0.94 | 0.95 |
| P4 | 0.86 | 0.84 | 0.86 | 0.84 | 0.90 |
| P5 | 0.91 | 0.91 | 0.91 | 0.92 | 0.92 |
| P6 | 0.94 | 0.93 | 0.94 | 0.94 | 0.95 |
| Group | accuracy_rs_mean_100 | accuracy_rs_mean_80 | accuracy_rs_mean_60 | accuracy_rs_mean_40 | accuracy_rs_mean_20 |
|---|---|---|---|---|---|
| P0 | 0.97 | 0.97 | 0.98 | 0.99 | 1.00 |
| P1 | 0.95 | 0.96 | 0.97 | 0.99 | 1.00 |
| P2 | 0.94 | 0.95 | 0.97 | 0.98 | 1.00 |
| P3 | 0.93 | 0.95 | 0.97 | 0.98 | 0.99 |
| P4 | 0.95 | 0.96 | 0.97 | 0.99 | 1.00 |
| P5 | 0.94 | 0.95 | 0.97 | 0.98 | 1.00 |
| P6 | 0.93 | 0.95 | 0.96 | 0.98 | 0.99 |
Sinvolle beschreibung des Plottes hier
Sinvolle beschreibung des Plottes hier
Sinvolle beschreibung des Plottes hier
Sinvolle beschreibung des Plottes hier
Sinvolle beschreibung des Plottes hier
Sinvolle Beschreibung des Plottes hier
Hier stimmt was mit den Daten nicht so ganz. Über all \(1\) drin.
Beschreibender Text hier.
Summary Table Recall
| Group | T_LDT_Recall_Mean | T_LDT_Recall_Median | S_LDT_Recall_Mean | S_LDT_Recall_Median |
|---|---|---|---|---|
| P0 | 1 | 1 | 1 | 1 |
| P1 | 1 | 1 | 1 | 1 |
| P2 | 1 | 1 | 1 | 1 |
| P3 | 1 | 1 | 1 | 1 |
| P4 | 1 | 1 | 1 | 1 |
| P5 | 1 | 1 | 1 | 1 |
| P6 | 1 | 1 | 1 | 1 |
Beschreibender Text hier.
Precision Summary
| Group | T_LDT_Precision_Mean | T_LDT_Precision_Median | S_LDT_Precision_Mean | S_LDT_Precision_Median |
|---|---|---|---|---|
| P0 | 0.05 | 0.01 | 0.07 | 0.00 |
| P1 | 0.09 | 0.04 | 0.10 | 0.04 |
| P2 | 0.13 | 0.09 | 0.18 | 0.11 |
| P3 | 0.14 | 0.10 | 0.23 | 0.18 |
| P4 | 0.09 | 0.04 | 0.10 | 0.04 |
| P5 | 0.12 | 0.08 | 0.17 | 0.11 |
| P6 | 0.14 | 0.10 | 0.20 | 0.13 |
Accuracy Beschreibender Text hier.
Accuracy Summary
| Group | T_LDT_Precision_Mean | T_LDT_Precision_Median | S_LDT_Precision_Mean | S_LDT_Precision_Median |
|---|---|---|---|---|
| P0 | 0.05 | 0.01 | 0.07 | 0.00 |
| P1 | 0.09 | 0.04 | 0.10 | 0.04 |
| P2 | 0.13 | 0.09 | 0.18 | 0.11 |
| P3 | 0.14 | 0.10 | 0.23 | 0.18 |
| P4 | 0.09 | 0.04 | 0.10 | 0.04 |
| P5 | 0.12 | 0.08 | 0.17 | 0.11 |
| P6 | 0.14 | 0.10 | 0.20 | 0.13 |
Recall: Beschreibender Text hier.
Precision: Beschreibender Text hier.
Accuracy: Beschreibender Text hier.
Tripple T Fraction: Beschreibender Text hier.
Tripple S Fraction: Beschreibender Text hier.